import numpy as np
import sys
from NuRadioMC.utilities.Veff import get_Veff_Aeff, get_Veff_Aeff_array
if __name__ == "__main__":
depth = ''
if(len(sys.argv) == 4):
print("no depth specified!")
sys.exit()
else:
depth = sys.argv[1]
top_dir='/data/user/brianclark/Gen2/test_out/'
data = get_Veff_Aeff(top_dir+depth+'m/', n_cores=8)
Veffs, energies, energies_low, energies_up, zenith_bins, utrigger_names = get_Veff_Aeff_array(data)
np.savez('veffs_'+depth+'m.npz',Veffs=Veffs, energies=energies, energies_low=energies_low, energies_up=energies_up, zenith_bins=zenith_bins, utrigger_names=utrigger_names)
"""
data_Veff = get_Veff_Aeff(folder)
"""
Although data_Veff has all the information we need, it is a bit cumbersome
to read directly, so that's why we resort to the function get_Veff_array. This
function returns a 5-element tuple with:
- An 4-D array with the effective volumes
- A 1-D array with the centre energies for each bin (if point_bins=False)
- The zenith bins for each one of the zenith band simulations (in our case, we
only have a single zenith band equal to the whole sky)
- A list with the trigger names
- A 1-D array with the angular weights for each zenith band simulation. If the solid
angle for a simulation set is larger than for the other, it should carry more weight
when we try to patch them all together to get the total volumes.
"""
Veff_array, energies, energies_low, energies_high, zenith_bins, trigger_names = get_Veff_Aeff_array(
data_Veff)
"""
There are some functions with the same syntax to calculate effective areas for
atmospheric muon simulations: get_Aeff and get_Aeff_array. Keep in mind that the
latter returns a 4-element tuple, with no weights.
The structure of the 4-D Veff_array returned is as follows: the first dimension
chooses the energy, the second chooses the zenith band and the third chooses
the trigger:
Veff_item = Veff_array[i_energy, i_zenith, i_trigger]
Then, each Veff_item has three numbers.
- Veff_item[0] is the effective volume
- Veff_item[1] is the poissonian uncertainty of the effective volume
- Veff_item[2] is the sum of the weights of all the triggering events contained
def get_flavor_zenith_averages(
det, det_dict): # det ('deep') and the associated dictionary
if 'trigger' not in det_dict.keys():
print("A trigger is not specified")
trigger = det_dict['trigger']
tmp = {} # a holder
tmp[trigger] = {}
for iF, flavor in enumerate(flavors):
# first, the low energies
filename = f'data__{deep_det}__{shallow_det}/{det}_{flavor}_lo.pkl'
data = pickle.load(open(filename, 'br'))
output, energies, energies_low, energies_up, zenith_bins, trigger_names = get_Veff_Aeff_array(
data)
if trigger not in trigger_names:
print("The requested trigger is not available. Options are {}".
format(trigger_names))
tmp['E'] = energies
tmp['zen_bins'] = zenith_bins
tmp[trigger][flavor] = {}
tmp[trigger][flavor][
'Veff_zen'] = output[:, :,
get_index(trigger, trigger_names), 0]
tmp[trigger][flavor]['Veff'] = np.average(
output[:, :, get_index(trigger, trigger_names), 0], axis=1)
tmp[trigger][flavor][
'Vefferror'] = tmp[trigger][flavor]['Veff'] / np.sum(
output[:, :, get_index(trigger, trigger_names),
2], axis=1)**0.5
tmp[trigger][flavor]['Vefferror_up'] = np.sum(
(output[:, :, get_index(trigger, trigger_names), 4] -
output[:, :, get_index(trigger, trigger_names), 0])**2,
axis=1)**0.5 / output.shape[1]
tmp[trigger][flavor]['Vefferror_down'] = np.sum(
(output[:, :, get_index(trigger, trigger_names), 0] -
output[:, :, get_index(trigger, trigger_names), 3])**2,
axis=1)**0.5 / output.shape[1]
# print("low energy energies {}".format(energies))
# print("low energy veffs {}".format(np.average(output[:, :, get_index(trigger, trigger_names), 0], axis=1)))
# print("low energy veffs vs zen {}".format(output[:, :, get_index(trigger, trigger_names), 0]))
# now, the high energies
filename = f'data__{deep_det}__{shallow_det}/{det}_{flavor}_hi.pkl'
data = pickle.load(open(filename, 'br'))
output, energies, energies_low, energies_up, zenith_bins, trigger_names = get_Veff_Aeff_array(
data)
if trigger not in trigger_names:
print("The requested trigger is not available. Options are {}".
format(trigger_names))
# Brian did something silly, and for the 1.5km station, his files accidentally contain an incorrect calculation for the low energies
# so we need to splice those away, which are index 0 (1E16), 1 (1E16.5), 2 (1E17), 3 (1E17.5), 4 (1E18)
start_splice_index = 0
if flavor == 'mu' and det == 'shallow' and shallow_det == 'surface_1.50km':
start_splice_index = 5
tmp['E'] = np.append(
tmp['E'], energies[start_splice_index:]
) # we assume we have the same energies simulated for each flavor
tmp[trigger][flavor]['Veff_zen'] = np.append(
tmp[trigger][flavor]['Veff_zen'],
output[:, :, get_index(trigger, trigger_names),
0][start_splice_index:])
tmp[trigger][flavor]['Veff'] = np.append(
tmp[trigger][flavor]['Veff'],
np.average(output[:, :, get_index(trigger, trigger_names), 0],
axis=1)[start_splice_index:])
tmp[trigger][flavor]['Vefferror'] = np.append(
tmp[trigger][flavor]['Vefferror'],
np.average(output[:, :, get_index(trigger, trigger_names), 0],
axis=1)[start_splice_index:] /
np.sum(output[:, :, get_index(trigger, trigger_names), 2],
axis=1)[start_splice_index:]**0.5)
tmp[trigger][flavor]['Vefferror_up'] = np.append(
tmp[trigger][flavor]['Vefferror_up'],
np.sum((output[:, :, get_index(trigger, trigger_names), 4] -
output[:, :, get_index(trigger, trigger_names),
0])[start_splice_index:]**2,
axis=1)**0.5 / output.shape[1])
tmp[trigger][flavor]['Vefferror_down'] = np.append(
tmp[trigger][flavor]['Vefferror_down'],
np.sum((output[:, :, get_index(trigger, trigger_names), 0] -
output[:, :, get_index(trigger, trigger_names),
3])[start_splice_index:]**2,
axis=1)**0.5 / output.shape[1])
# print("high energy energies {}".format(energies[start_splice_index:]))
# print("high energy veffs {}".format(np.average(output[:, :, get_index(trigger, trigger_names), 0], axis=1)[start_splice_index:]))
# print("\n")
# do the flavor average
tmp[trigger]['Veff'] = 0
tmp[trigger]['Vefferror'] = 0
tmp[trigger]['Vefferror_down'] = 0
tmp[trigger]['Vefferror_up'] = 0
tmp[trigger]['Veff_zen'] = 0
for flavor in flavors:
tmp[trigger]['Veff'] += tmp[trigger][flavor]['Veff']
tmp[trigger]['Vefferror'] += tmp[trigger][flavor]['Vefferror']
tmp[trigger]['Veff_zen'] += tmp[trigger][flavor]['Veff_zen']
tmp[trigger]['Vefferror_up'] += tmp[trigger][flavor]['Vefferror_up']**2
tmp[trigger]['Vefferror_down'] += tmp[trigger][flavor][
'Vefferror_down']**2
tmp[trigger]['Vefferror'] /= 3
tmp[trigger]['Veff_zen'] /= 3
tmp[trigger]['Veff'] /= 3
tmp[trigger]['Vefferror_up'] = tmp[trigger]['Vefferror_up']**0.5 / 3
tmp[trigger]['Vefferror_down'] = tmp[trigger]['Vefferror_down']**0.5 / 3
return tmp